



import unittest
from dataclasses import dataclass

import pytest

from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict






@dataclass
class  SCREAMING_SNAKE_CASE      (				snake_case_       ):
							__lowerCamelCase						:						int     =ComputeEnvironment.AMAZON_SAGEMAKER
							__lowerCamelCase						:						Tuple     =True
							__lowerCamelCase						:						Optional[int]     ='ml.p3.2xlarge'
							__lowerCamelCase						:						List[Any]     ='accelerate_sagemaker_execution_role'
							__lowerCamelCase						:						Any     ='hf-sm'
							__lowerCamelCase						:						Any     ='us-east-1'
							__lowerCamelCase						:						str     =1
							__lowerCamelCase						:						List[Any]     ='accelerate-sagemaker-1'
							__lowerCamelCase						:						Tuple     ='1.6'
							__lowerCamelCase						:						Optional[Any]     ='4.4'
							__lowerCamelCase						:						List[Any]     ='train.py'
							__lowerCamelCase						:						Tuple     =[
							    '--model_name_or_path',
							    'bert',
							    '--do_train',
							    'False',
							    '--epochs',
							    '3',
							    '--learning_rate',
							    '5e-5',
							    '--max_steps',
							    '50.5',
							]
							__lowerCamelCase						:						Any     =[
							    '--model_name_or_path',
							    'bert',
							    '--do_train',
							    '--do_test',
							    'False',
							    '--do_predict',
							    '--epochs',
							    '3',
							    '--learning_rate',
							    '5e-5',
							    '--max_steps',
							    '50.5',
							]






class  SCREAMING_SNAKE_CASE      (				unittest.TestCase       ):





							def     UpperCamelCase_       ( self		:		Optional[Any]						):

											'''simple docstring'''
											__a	  =		_convert_nargs_to_dict(MockLaunchConfig.success_training_script_args						)
											assert isinstance(converted_args["""model_name_or_path"""]   ,					lowerCAmelCase__						)
											assert isinstance(converted_args["""do_train"""]   ,					lowerCAmelCase__						)
											assert isinstance(converted_args["""epochs"""]   ,					lowerCAmelCase__						)
											assert isinstance(converted_args["""learning_rate"""]   ,					lowerCAmelCase__						)
											assert isinstance(converted_args["""max_steps"""]   ,					lowerCAmelCase__						)

											with pytest.raises(lowerCAmelCase__						):
															_convert_nargs_to_dict(MockLaunchConfig.fail_training_script_args						)





'''simple docstring'''



import argparse
from collections import defaultdict

import yaml


lowerCAmelCase_  :							Tuple             =    'docs/source/en/_toctree.yml'
def        UpperCAmelCase (    A	:					Union[str, Any]					):
							SCREAMING_SNAKE_CASE       :   Dict         =      defaultdict(A					)
							for doc in model_doc:
														counts[doc["local"]] += 1
							SCREAMING_SNAKE_CASE       :   Tuple         =      [key for key, value in counts.items() if value > 1]

							SCREAMING_SNAKE_CASE       :   Tuple         =      []
							for duplicate_key in duplicates:
														SCREAMING_SNAKE_CASE       :   Optional[int]         =      list({doc['''title'''] for doc in model_doc if doc['''local'''] == duplicate_key}					)
														if len(A					) > 1:
																					raise ValueError(
																					    F"""{duplicate_key} is present several times in the documentation table of content at """
																					    '''`docs/source/en/_toctree.yml` with different *Title* values. Choose one of those and remove the '''
																					    '''others.'''					)
														# Only add this once
														new_doc.append({'''local''': duplicate_key, '''title''': titles[0]}					)

							# Add none duplicate-keys
							new_doc.extend([doc for doc in model_doc if counts[doc['''local''']] == 1]					)

							# Sort
							return sorted(A       ,		key=lambda A					: s["title"].lower()					)
def        UpperCAmelCase (    A	:					Any=False					):
							with open(A       ,		encoding='''utf-8'''					) as f:
														SCREAMING_SNAKE_CASE       :   str         =      yaml.safe_load(f.read()					)

							# Get to the API doc
							SCREAMING_SNAKE_CASE       :   Any         =      0
							while content[api_idx]["title"] != "API":
														api_idx += 1
							SCREAMING_SNAKE_CASE       :   Dict         =      content[api_idx]['''sections''']

							# Then to the model doc
							SCREAMING_SNAKE_CASE       :   List[str]         =      0
							while api_doc[model_idx]["title"] != "Models":
														model_idx += 1

							SCREAMING_SNAKE_CASE       :   Dict         =      api_doc[model_idx]['''sections''']

							SCREAMING_SNAKE_CASE       :   List[Any]         =      [(idx, section) for idx, section in enumerate(A					) if '''sections''' in section]
							SCREAMING_SNAKE_CASE       :   int         =      False
							for idx, modality_doc in modalities_docs:
														SCREAMING_SNAKE_CASE       :   List[str]         =      modality_doc['''sections''']
														SCREAMING_SNAKE_CASE       :   List[str]         =      clean_model_doc_toc(A					)

														if old_modality_doc != new_modality_doc:
																					SCREAMING_SNAKE_CASE       :   Dict         =      True
																					if overwrite:
																												SCREAMING_SNAKE_CASE       :   int         =      new_modality_doc

							if diff:
														if overwrite:
																					SCREAMING_SNAKE_CASE       :   List[Any]         =      model_doc
																					SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      api_doc
																					with open(A       ,		'''w'''       ,		encoding='''utf-8'''					) as f:
																												f.write(yaml.dump(A       ,		allow_unicode=A					)					)
														else:
																					raise ValueError(
																					    '''The model doc part of the table of content is not properly sorted, run `make style` to fix this.'''					)


if __name__ == "__main__":
							lowerCAmelCase_  :							Optional[int]             =    argparse.ArgumentParser()
							parser.add_argument('--fix_and_overwrite', action='store_true', help='Whether to fix inconsistencies.')
							lowerCAmelCase_  :							Any             =    parser.parse_args()

							check_model_doc(args.fix_and_overwrite)




